{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\J.PARK\Dropbox\Discrimination Project_for me\Organizational Diversity\2023 Version_Merging\FINAL\CFA_2014.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 8 Aug 2024, 13:20:37
{txt}
{com}. 
. 
. import delimited "C:\Users\J.PARK\Dropbox\DISCRIMINATION PROJECT\FEVS\FEVS_2010-2019\FEVS2014_PRDF.csv"
{res}{txt}(encoding automatically selected: ISO-8859-1)
{res}{text}(100 vars, 392,752 obs)

{com}. drop if q17=="X"
{txt}(16,950 observations deleted)

{com}. drop if q17==""
{txt}(2,708 observations deleted)

{com}. drop if q37=="X"
{txt}(17,214 observations deleted)

{com}. drop if q37==""
{txt}(8,948 observations deleted)

{com}. drop if q38=="X"
{txt}(16,630 observations deleted)

{com}. drop if q38==""
{txt}(3,530 observations deleted)

{com}. drop if q15=="X"
{txt}(2,511 observations deleted)

{com}. drop if q15==""
{txt}(1,200 observations deleted)

{com}. drop if q22=="X"
{txt}(12,769 observations deleted)

{com}. drop if q22==""
{txt}(2,626 observations deleted)

{com}. drop if q25=="X"
{txt}(7,379 observations deleted)

{com}. drop if q25==""
{txt}(1,579 observations deleted)

{com}. drop if q33=="X"
{txt}(5,929 observations deleted)

{com}. drop if q33==""
{txt}(2,765 observations deleted)

{com}. drop if q48==.
{txt}(2,735 observations deleted)

{com}. drop if q49==.
{txt}(1,123 observations deleted)

{com}. destring q17, replace
{txt}q17: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q37, replace
{txt}q37: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q38, replace
{txt}q38: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q15, replace
{txt}q15: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q22, replace
{txt}q22: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q25, replace
{txt}q25: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q33, replace
{txt}q33: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. drop if q55=="X"
{txt}(6,258 observations deleted)

{com}. drop if q55==""
{txt}(4,797 observations deleted)

{com}. drop if q45=="X"
{txt}(7,788 observations deleted)

{com}. drop if q45==""
{txt}(1,020 observations deleted)

{com}. drop if q34=="X"
{txt}(4,669 observations deleted)

{com}. drop if q34==""
{txt}(909 observations deleted)

{com}. destring q55, replace
{txt}q55: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q45, replace
{txt}q45: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. destring q34, replace
{txt}q34: all characters numeric; {res}replaced {txt}as {res}byte
{txt}
{com}. drop if dsuper=="X"
{txt}(0 observations deleted)

{com}. drop if dsuper==""
{txt}(10,260 observations deleted)

{com}. drop if dsex=="X"
{txt}(0 observations deleted)

{com}. drop if dsex==""
{txt}(4,643 observations deleted)

{com}. drop if dminority==.
{txt}(7,509 observations deleted)

{com}. gen minority = 0 if dminority==2
{txt}(81,962 missing values generated)

{com}. replace minority = 1 if dminority==1
{txt}(81,962 real changes made)

{com}. gen gender = 1 if dsex == "B"
{txt}(127,540 missing values generated)

{com}. replace gender = 0 if dsex == "A"
{txt}(127,540 real changes made)

{com}. gen supervisor = 1 if dsuper == "B" 
{txt}(180,043 missing values generated)

{com}. replace supervisor = 0 if dsuper == "A"
{txt}(180,043 real changes made)

{com}. svyset [pweight=postwt]

{txt}Sampling weights:{col 19}{res}postwt
             {txt}VCE:{col 19}{res}linearized
     {txt}Single unit:{col 19}{res}missing
        {txt}Strata 1:{col 19}<one>
 Sampling unit 1:{col 19}<observations>
           FPC 1:{col 19}<zero>
{p2colreset}{...}

{com}. 
. svy linearized : sem (JUSTICE -> DISTRIBUTIVE, ) (JUSTICE -> PROCEDURAL, ) (JUSTICE -> INTERPERSONAL, ) (DISTRIBUTIVE -> q22, ) (DISTRIBUTIVE -> q25, ) (DISTRIBUTIVE -> q33, ) (PROCEDURAL -> q15, ) (PROCEDURAL -> q17, ) (PROCEDURAL -> q37, ) (PROCEDURAL -> q38, )(INTERPERSONAL -> q48, ) (INTERPERSONAL -> q49, ), standardized latent(JUSTICE DISTRIBUTIVE PROCEDURAL INTERPERSONAL ) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:238,303}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,093,889}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:238,303}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:238,302}

{p 0 7}{space 1}{text:( 1)}{space 1} [q22]DISTRIBUTIVE = 1{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [q15]PROCEDURAL = 1{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [q48]INTERPERSONAL = 1{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [DISTRIBUTIVE]JUSTICE = 1{p_end}
{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}  Linearized
{col 1}       Standardized{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural         {col 21}{txt}{c |}
{space 2}{col 3}DISTRIBUTIVE     {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .8452832{col 33}{space 2} .0019222{col 44}{space 1}  439.75{col 53}{space 3}0.000{col 61}{space 4} .8415158{col 74}{space 3} .8490506
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}PROCEDURAL       {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .9801897{col 33}{space 2} .0020428{col 44}{space 1}  479.82{col 53}{space 3}0.000{col 61}{space 4} .9761858{col 74}{space 3} .9841936
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}INTERPERSONAL    {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .6986292{col 33}{space 2} .0022455{col 44}{space 1}  311.12{col 53}{space 3}0.000{col 61}{space 4}  .694228{col 74}{space 3} .7030303
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement        {col 21}{txt}{c |}
{space 2}{col 3}q22              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8420109{col 33}{space 2} .0014302{col 44}{space 1}  588.72{col 53}{space 3}0.000{col 61}{space 4} .8392076{col 74}{space 3} .8448141
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.352933{col 33}{space 2} .0048247{col 44}{space 1}  487.69{col 53}{space 3}0.000{col 61}{space 4} 2.343477{col 74}{space 3} 2.362389
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q25              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8364203{col 33}{space 2} .0014523{col 44}{space 1}  575.94{col 53}{space 3}0.000{col 61}{space 4} .8335739{col 74}{space 3} .8392667
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  2.41583{col 33}{space 2} .0051426{col 44}{space 1}  469.77{col 53}{space 3}0.000{col 61}{space 4}  2.40575{col 74}{space 3} 2.425909
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q33              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .7108091{col 33}{space 2}  .001923{col 44}{space 1}  369.64{col 53}{space 3}0.000{col 61}{space 4} .7070402{col 74}{space 3}  .714578
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.149724{col 33}{space 2} .0038761{col 44}{space 1}  554.62{col 53}{space 3}0.000{col 61}{space 4} 2.142127{col 74}{space 3} 2.157321
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q15              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2}  .613528{col 33}{space 2} .0026845{col 44}{space 1}  228.54{col 53}{space 3}0.000{col 61}{space 4} .6082664{col 74}{space 3} .6187896
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.203406{col 33}{space 2} .0091148{col 44}{space 1}  351.45{col 53}{space 3}0.000{col 61}{space 4} 3.185541{col 74}{space 3} 3.221271
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q17              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .7554244{col 33}{space 2} .0018873{col 44}{space 1}  400.26{col 53}{space 3}0.000{col 61}{space 4} .7517253{col 74}{space 3} .7591235
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.895103{col 33}{space 2} .0075459{col 44}{space 1}  383.67{col 53}{space 3}0.000{col 61}{space 4} 2.880314{col 74}{space 3} 2.909893
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q37              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8338122{col 33}{space 2} .0015966{col 44}{space 1}  522.24{col 53}{space 3}0.000{col 61}{space 4} .8306829{col 74}{space 3} .8369415
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.666773{col 33}{space 2} .0064466{col 44}{space 1}  413.67{col 53}{space 3}0.000{col 61}{space 4} 2.654138{col 74}{space 3} 2.679408
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q38              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8119691{col 33}{space 2} .0017511{col 44}{space 1}  463.70{col 53}{space 3}0.000{col 61}{space 4}  .808537{col 74}{space 3} .8154011
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.252085{col 33}{space 2}  .009295{col 44}{space 1}  349.87{col 53}{space 3}0.000{col 61}{space 4} 3.233867{col 74}{space 3} 3.270303
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q48              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9401321{col 33}{space 2} .0012203{col 44}{space 1}  770.41{col 53}{space 3}0.000{col 61}{space 4} .9377404{col 74}{space 3} .9425239
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.711019{col 33}{space 2}  .011349{col 44}{space 1}  326.99{col 53}{space 3}0.000{col 61}{space 4} 3.688776{col 74}{space 3} 3.733263
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q49              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9169585{col 33}{space 2} .0012997{col 44}{space 1}  705.50{col 53}{space 3}0.000{col 61}{space 4} .9144111{col 74}{space 3} .9195059
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 4.006309{col 33}{space 2} .0133917{col 44}{space 1}  299.16{col 53}{space 3}0.000{col 61}{space 4} 3.980062{col 74}{space 3} 4.032556
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}var(e.q22){c |}{col 21}{res}{space 2} .2910177{col 33}{space 2} .0024085{col 61}{space 4} .2863351{col 74}{space 3} .2957769
{txt}{space 10}var(e.q25){c |}{col 21}{res}{space 2} .3004011{col 33}{space 2} .0024294{col 61}{space 4} .2956771{col 74}{space 3} .3052006
{txt}{space 10}var(e.q33){c |}{col 21}{res}{space 2} .4947504{col 33}{space 2} .0027337{col 61}{space 4} .4894213{col 74}{space 3} .5001375
{txt}{space 10}var(e.q15){c |}{col 21}{res}{space 2} .6235834{col 33}{space 2} .0032941{col 61}{space 4} .6171604{col 74}{space 3} .6300733
{txt}{space 10}var(e.q17){c |}{col 21}{res}{space 2}  .429334{col 33}{space 2} .0028514{col 61}{space 4} .4237814{col 74}{space 3} .4349593
{txt}{space 10}var(e.q37){c |}{col 21}{res}{space 2} .3047572{col 33}{space 2} .0026625{col 61}{space 4} .2995831{col 74}{space 3} .3100206
{txt}{space 10}var(e.q38){c |}{col 21}{res}{space 2} .3407062{col 33}{space 2} .0028436{col 61}{space 4} .3351781{col 74}{space 3} .3463255
{txt}{space 10}var(e.q48){c |}{col 21}{res}{space 2} .1161516{col 33}{space 2} .0022945{col 61}{space 4} .1117404{col 74}{space 3} .1207369
{txt}{space 10}var(e.q49){c |}{col 21}{res}{space 2} .1591872{col 33}{space 2} .0023836{col 61}{space 4} .1545833{col 74}{space 3} .1639281
{txt}{space 1}var(e.DISTRIBUTIVE){c |}{col 21}{res}{space 2} .2854964{col 33}{space 2} .0032496{col 61}{space 4} .2791978{col 74}{space 3}  .291937
{txt}{space 3}var(e.PROCEDURAL){c |}{col 21}{res}{space 2} .0392281{col 33}{space 2} .0040047{col 61}{space 4} .0321144{col 74}{space 3} .0479176
{txt}var(e.INTERPERSONAL){c |}{col 21}{res}{space 2} .5119173{col 33}{space 2} .0031376{col 61}{space 4} .5058045{col 74}{space 3} .5181039
{txt}{space 8}var(JUSTICE){c |}{col 21}{res}{space 2}        1{col 33}{space 2}        .{col 61}{space 4}        .{col 74}{space 3}        .
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.041}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.965}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict justice, latent(JUSTICE)
{res}{txt}
{com}. 
. svy linearized : sem (DIVERSITY -> q34, ) (DIVERSITY -> q45, ) (DIVERSITY -> q55, ), standardized latent(DIVERSITY) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:238,303}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,093,889}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:238,303}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:238,302}

{p 0 7}{space 1}{text:( 1)}{space 1} [q34]DIVERSITY = 1{p_end}
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}  Linearized
{col 1} Standardized{col 15}{c |} Coefficient{col 27}  std. err.{col 39}      t{col 47}   P>|t|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement  {col 15}{txt}{c |}
{space 2}{col 3}q34        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .6744894{col 27}{space 2} .0027629{col 38}{space 1}  244.12{col 47}{space 3}0.000{col 55}{space 4} .6690742{col 68}{space 3} .6799046
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}    3.297{col 27}{space 2} .0089495{col 38}{space 1}  368.40{col 47}{space 3}0.000{col 55}{space 4} 3.279459{col 68}{space 3} 3.314541
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q45        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .7535209{col 27}{space 2} .0026357{col 38}{space 1}  285.89{col 47}{space 3}0.000{col 55}{space 4}  .748355{col 68}{space 3} .7586869
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.525162{col 27}{space 2} .0102618{col 38}{space 1}  343.52{col 47}{space 3}0.000{col 55}{space 4}  3.50505{col 68}{space 3} 3.545275
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q55        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2}   .81678{col 27}{space 2} .0024661{col 38}{space 1}  331.20{col 47}{space 3}0.000{col 55}{space 4} .8119464{col 68}{space 3} .8216135
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.430862{col 27}{space 2} .0097654{col 38}{space 1}  351.33{col 47}{space 3}0.000{col 55}{space 4} 3.411722{col 68}{space 3} 3.450002
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.q34){c |}{col 15}{res}{space 2} .5450641{col 27}{space 2} .0037271{col 55}{space 4} .5378078{col 68}{space 3} .5524183
{txt}{space 4}var(e.q45){c |}{col 15}{res}{space 2} .4322062{col 27}{space 2} .0039722{col 55}{space 4} .4244905{col 68}{space 3} .4400621
{txt}{space 4}var(e.q55){c |}{col 15}{res}{space 2} .3328705{col 27}{space 2} .0040286{col 55}{space 4} .3250675{col 68}{space 3} .3408608
{txt}var(DIVERSITY){c |}{col 15}{res}{space 2}        1{col 27}{space 2}        .{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.000}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.806}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict diversity, latent(DIVERSITY)
{res}{txt}
{com}. 
. keep if agency =="AM" | agency =="ED" | agency =="DN" | agency =="HU" | agency =="ST" | agency =="EP"  | agency =="FC" | agency =="GS" | agency =="NN" | agency =="NU" | agency =="OM" | agency =="SE" | agency =="SZ" | plevel1 =="DD34" | plevel1 =="DD10" | plevel1 =="DD63" | plevel1 =="DD35" | plevel1 =="DD04" | plevel1 =="DD07" | plevel1 =="DD27" | plevel1 =="DD60" | plevel2 =="AG1001" | plevel2 =="AG0101" | plevel2 =="AG0401" | plevel2 =="AG0501" | plevel2 =="AG0502" | plevel1 =="CM03"  | plevel1 =="CM08" | plevel1 =="CM09" | plevel1 =="CM14" | plevel1 =="HE04" | plevel1 =="HE05" | plevel1 =="HE06" | plevel1 =="HE08" | plevel1 =="HE09" | plevel1 =="HE10" | plevel1 =="HS04" | plevel1 =="HS14" | plevel1 =="HS01" | plevel1 =="HS03" | plevel1 =="HS02" | plevel1 =="HS06" | plevel1 =="HS12" | plevel1 =="DJ15" | plevel1 =="DJ03" | plevel1 =="DJEA" | plevel1 =="DJ09" | plevel1 =="DJ02" | plevel1 =="DJ08" | plevel1 =="DL03" | agency =="AF" | agency =="AR" | plevel1 =="IN03" | plevel1 =="IN01" | plevel1 =="IN02" | plevel1 =="IN07" | plevel1 =="IN05" | plevel1 =="IN06" | agency =="NV" | plevel1 =="TR93" | plevel1 =="TRAJ" | plevel1 =="TD03" | plevel1 =="TD04" | plevel1 =="VA04" | plevel1 =="VA03" | plevel1 =="VA02"
{txt}(34,418 observations deleted)

{com}. 
. svy linearized : sem (JUSTICE -> DISTRIBUTIVE, ) (JUSTICE -> PROCEDURAL, ) (JUSTICE -> INTERPERSONAL, ) (DISTRIBUTIVE -> q22, ) (DISTRIBUTIVE -> q25, ) (DISTRIBUTIVE -> q33, ) (PROCEDURAL -> q15, ) (PROCEDURAL -> q17, ) (PROCEDURAL -> q37, ) (PROCEDURAL -> q38, )(INTERPERSONAL -> q48, ) (INTERPERSONAL -> q49, ), standardized latent(JUSTICE DISTRIBUTIVE PROCEDURAL INTERPERSONAL ) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:203,885}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,018,280}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:203,885}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:203,884}

{p 0 7}{space 1}{text:( 1)}{space 1} [q22]DISTRIBUTIVE = 1{p_end}
{p 0 7}{space 1}{text:( 2)}{space 1} [q15]PROCEDURAL = 1{p_end}
{p 0 7}{space 1}{text:( 3)}{space 1} [q48]INTERPERSONAL = 1{p_end}
{p 0 7}{space 1}{text:( 4)}{space 1} [DISTRIBUTIVE]JUSTICE = 1{p_end}
{txt}{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}  Linearized
{col 1}       Standardized{col 21}{c |} Coefficient{col 33}  std. err.{col 45}      t{col 53}   P>|t|{col 61}     [95% con{col 74}f. interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Structural         {col 21}{txt}{c |}
{space 2}{col 3}DISTRIBUTIVE     {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .8436778{col 33}{space 2} .0020449{col 44}{space 1}  412.58{col 53}{space 3}0.000{col 61}{space 4} .8396698{col 74}{space 3} .8476857
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}PROCEDURAL       {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .9813239{col 33}{space 2} .0021747{col 44}{space 1}  451.24{col 53}{space 3}0.000{col 61}{space 4} .9770615{col 74}{space 3} .9855864
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}INTERPERSONAL    {col 21}{c |}
{space 12}JUSTICE {c |}{col 21}{res}{space 2} .6980319{col 33}{space 2} .0023858{col 44}{space 1}  292.58{col 53}{space 3}0.000{col 61}{space 4} .6933558{col 74}{space 3}  .702708
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement        {col 21}{txt}{c |}
{space 2}{col 3}q22              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8410618{col 33}{space 2} .0015248{col 44}{space 1}  551.59{col 53}{space 3}0.000{col 61}{space 4} .8380732{col 74}{space 3} .8440504
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.350041{col 33}{space 2}  .005088{col 44}{space 1}  461.88{col 53}{space 3}0.000{col 61}{space 4} 2.340069{col 74}{space 3} 2.360013
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q25              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .8362964{col 33}{space 2} .0015404{col 44}{space 1}  542.92{col 53}{space 3}0.000{col 61}{space 4} .8332773{col 74}{space 3} .8393155
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.412755{col 33}{space 2} .0054245{col 44}{space 1}  444.79{col 53}{space 3}0.000{col 61}{space 4} 2.402123{col 74}{space 3} 2.423387
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q33              {col 21}{c |}
{space 7}DISTRIBUTIVE {c |}{col 21}{res}{space 2} .7093006{col 33}{space 2}  .002048{col 44}{space 1}  346.34{col 53}{space 3}0.000{col 61}{space 4} .7052866{col 74}{space 3} .7133146
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.143959{col 33}{space 2} .0040796{col 44}{space 1}  525.54{col 53}{space 3}0.000{col 61}{space 4} 2.135963{col 74}{space 3} 2.151955
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q15              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .6114863{col 33}{space 2}  .002854{col 44}{space 1}  214.25{col 53}{space 3}0.000{col 61}{space 4} .6058925{col 74}{space 3} .6170801
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.204258{col 33}{space 2} .0096641{col 44}{space 1}  331.56{col 53}{space 3}0.000{col 61}{space 4} 3.185317{col 74}{space 3} 3.223199
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q17              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .7533176{col 33}{space 2} .0020121{col 44}{space 1}  374.39{col 53}{space 3}0.000{col 61}{space 4}  .749374{col 74}{space 3} .7572613
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.900839{col 33}{space 2} .0080248{col 44}{space 1}  361.48{col 53}{space 3}0.000{col 61}{space 4}  2.88511{col 74}{space 3} 2.916567
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q37              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8330937{col 33}{space 2} .0017005{col 44}{space 1}  489.92{col 53}{space 3}0.000{col 61}{space 4} .8297608{col 74}{space 3} .8364266
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 2.669155{col 33}{space 2} .0068431{col 44}{space 1}  390.05{col 53}{space 3}0.000{col 61}{space 4} 2.655743{col 74}{space 3} 2.682568
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q38              {col 21}{c |}
{space 9}PROCEDURAL {c |}{col 21}{res}{space 2} .8102405{col 33}{space 2} .0018678{col 44}{space 1}  433.80{col 53}{space 3}0.000{col 61}{space 4} .8065797{col 74}{space 3} .8139013
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.260401{col 33}{space 2} .0098921{col 44}{space 1}  329.60{col 53}{space 3}0.000{col 61}{space 4} 3.241012{col 74}{space 3} 3.279789
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q48              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9400001{col 33}{space 2} .0012966{col 44}{space 1}  724.99{col 53}{space 3}0.000{col 61}{space 4} .9374588{col 74}{space 3} .9425413
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 3.707443{col 33}{space 2} .0119863{col 44}{space 1}  309.31{col 53}{space 3}0.000{col 61}{space 4}  3.68395{col 74}{space 3} 3.730935
{space 2}{txt}{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q49              {col 21}{c |}
{space 6}INTERPERSONAL {c |}{col 21}{res}{space 2} .9164818{col 33}{space 2} .0013796{col 44}{space 1}  664.30{col 53}{space 3}0.000{col 61}{space 4} .9137777{col 74}{space 3} .9191858
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} 4.008115{col 33}{space 2} .0141843{col 44}{space 1}  282.57{col 53}{space 3}0.000{col 61}{space 4} 3.980314{col 74}{space 3} 4.035916
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}var(e.q22){c |}{col 21}{res}{space 2}  .292615{col 33}{space 2} .0025649{col 61}{space 4} .2876308{col 74}{space 3} .2976856
{txt}{space 10}var(e.q25){c |}{col 21}{res}{space 2} .3006084{col 33}{space 2} .0025764{col 61}{space 4} .2956008{col 74}{space 3} .3057008
{txt}{space 10}var(e.q33){c |}{col 21}{res}{space 2} .4968927{col 33}{space 2} .0029053{col 61}{space 4} .4912309{col 74}{space 3} .5026197
{txt}{space 10}var(e.q15){c |}{col 21}{res}{space 2} .6260845{col 33}{space 2} .0034904{col 61}{space 4} .6192807{col 74}{space 3} .6329631
{txt}{space 10}var(e.q17){c |}{col 21}{res}{space 2} .4325125{col 33}{space 2} .0030315{col 61}{space 4} .4266114{col 74}{space 3} .4384952
{txt}{space 10}var(e.q37){c |}{col 21}{res}{space 2} .3059549{col 33}{space 2} .0028333{col 61}{space 4} .3004517{col 74}{space 3} .3115588
{txt}{space 10}var(e.q38){c |}{col 21}{res}{space 2} .3435103{col 33}{space 2} .0030267{col 61}{space 4}  .337629{col 74}{space 3} .3494942
{txt}{space 10}var(e.q48){c |}{col 21}{res}{space 2} .1163999{col 33}{space 2} .0024375{col 61}{space 4} .1117191{col 74}{space 3} .1212768
{txt}{space 10}var(e.q49){c |}{col 21}{res}{space 2} .1600611{col 33}{space 2} .0025288{col 61}{space 4} .1551807{col 74}{space 3} .1650951
{txt}{space 1}var(e.DISTRIBUTIVE){c |}{col 21}{res}{space 2} .2882079{col 33}{space 2} .0034505{col 61}{space 4} .2815237{col 74}{space 3} .2950507
{txt}{space 3}var(e.PROCEDURAL){c |}{col 21}{res}{space 2} .0370034{col 33}{space 2} .0042683{col 61}{space 4} .0295159{col 74}{space 3} .0463902
{txt}var(e.INTERPERSONAL){c |}{col 21}{res}{space 2} .5127515{col 33}{space 2} .0033307{col 61}{space 4} .5062647{col 74}{space 3} .5193214
{txt}{space 8}var(JUSTICE){c |}{col 21}{res}{space 2}        1{col 33}{space 2}        .{col 61}{space 4}        .{col 74}{space 3}        .
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.040}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.967}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict justice2, latent (JUSTICE)
{res}{txt}
{com}. 
. svy linearized : sem (DIVERSITY -> q34, ) (DIVERSITY -> q45, ) (DIVERSITY -> q55, ), standardized latent(DIVERSITY) nocapslatent
{res}{txt}(running {bf:sem} on estimation sample)
{res}
{txt}{col 1}Survey: Structural equation model{col 52}{lalign 15:Number of obs}{col 67} = {res}{ralign 9:203,885}
{txt}{col 1}{lalign 16:Number of strata}{col 17} = {res}{ralign 7:1}{txt}{col 52}{lalign 15:Population size}{col 67} = {res}{ralign 9:1,018,280}
{txt}{col 1}{lalign 16:Number of PSUs}{col 17} = {res}{ralign 7:203,885}{txt}{col 52}{lalign 15:Design df}{col 67} = {res}{ralign 9:203,884}

{p 0 7}{space 1}{text:( 1)}{space 1} [q34]DIVERSITY = 1{p_end}
{txt}{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}  Linearized
{col 1} Standardized{col 15}{c |} Coefficient{col 27}  std. err.{col 39}      t{col 47}   P>|t|{col 55}     [95% con{col 68}f. interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}{res}Measurement  {col 15}{txt}{c |}
{space 2}{col 3}q34        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .6713787{col 27}{space 2} .0029428{col 38}{space 1}  228.14{col 47}{space 3}0.000{col 55}{space 4} .6656109{col 68}{space 3} .6771465
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.304842{col 27}{space 2} .0095274{col 38}{space 1}  346.88{col 47}{space 3}0.000{col 55}{space 4} 3.286169{col 68}{space 3} 3.323515
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q45        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .7540155{col 27}{space 2}   .00281{col 38}{space 1}  268.34{col 47}{space 3}0.000{col 55}{space 4}  .748508{col 68}{space 3} .7595229
{txt}{space 8}_cons {c |}{col 15}{res}{space 2}  3.52198{col 27}{space 2} .0108454{col 38}{space 1}  324.74{col 47}{space 3}0.000{col 55}{space 4} 3.500723{col 68}{space 3} 3.543237
{space 2}{txt}{hline 12}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}{col 3}q55        {col 15}{c |}
{space 4}DIVERSITY {c |}{col 15}{res}{space 2} .8158732{col 27}{space 2} .0026294{col 38}{space 1}  310.29{col 47}{space 3}0.000{col 55}{space 4} .8107196{col 68}{space 3} .8210267
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} 3.440589{col 27}{space 2} .0104074{col 38}{space 1}  330.59{col 47}{space 3}0.000{col 55}{space 4} 3.420191{col 68}{space 3} 3.460988
{txt}{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}var(e.q34){c |}{col 15}{res}{space 2} .5492506{col 27}{space 2} .0039515{col 55}{space 4} .5415602{col 68}{space 3} .5570502
{txt}{space 4}var(e.q45){c |}{col 15}{res}{space 2} .4314607{col 27}{space 2} .0042375{col 55}{space 4} .4232347{col 68}{space 3} .4398466
{txt}{space 4}var(e.q55){c |}{col 15}{res}{space 2}  .334351{col 27}{space 2} .0042905{col 55}{space 4} .3260466{col 68}{space 3} .3428669
{txt}var(DIVERSITY){c |}{col 15}{res}{space 2}        1{col 27}{space 2}        .{col 55}{space 4}        .{col 68}{space 3}        .
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. estat gof, stats(all)
{res}
{txt}{hline 21}{c TT}{hline 54}
{lalign 21:Fit statistic}{c |}      Value   Description
{hline 21}{c +}{hline 54}
{lalign 21:Size of residuals}{c |}
{ralign 20:SRMR} {c |} {res}{ralign 10:     0.000}{txt}   Standardized root mean squared residual
{ralign 20:CD} {c |} {res}{ralign 10:     0.805}{txt}   Coefficient of determination
{hline 21}{c BT}{hline 54}
{p 0 2 2 75}Note: model was fit with{txt} svy: prefix; only stats(residuals) valid.{p_end}

{com}. 
. predict diversity2, latent (DIVERSITY)
{res}{txt}
{com}. 
. sum justice, detail

                   {txt}Factor score (JUSTICE)
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.074657       -2.18605
{txt} 5%    {res}-1.566219       -2.18605
{txt}10%    {res}-1.130207       -2.18605       {txt}Obs         {res}    203,885
{txt}25%    {res}-.4110456       -2.18605       {txt}Sum of wgt. {res}    203,885

{txt}50%    {res} .1985977                      {txt}Mean          {res} .0602153
                        {txt}Largest       Std. dev.     {res} .8133328
{txt}75%    {res} .6070213       1.363959
{txt}90%    {res} 1.055386       1.363959       {txt}Variance      {res} .6615102
{txt}95%    {res} 1.243078       1.363959       {txt}Skewness      {res}-.6495034
{txt}99%    {res} 1.363959       1.363959       {txt}Kurtosis      {res} 2.961799
{txt}
{com}. 
. sum justice2, detail

                   {txt}Factor score (JUSTICE)
{hline 61}
      Percentiles      Smallest
 1%    {res}-2.067802      -2.178193
{txt} 5%    {res}-1.561037      -2.178193
{txt}10%    {res}-1.125353      -2.178193       {txt}Obs         {res}    203,885
{txt}25%    {res}-.4080204      -2.178193       {txt}Sum of wgt. {res}    203,885

{txt}50%    {res} .2014075                      {txt}Mean          {res} .0629807
                        {txt}Largest       Std. dev.     {res} .8115224
{txt}75%    {res} .6066566       1.362152
{txt}90%    {res} 1.054515       1.362152       {txt}Variance      {res} .6585686
{txt}95%    {res} 1.241564       1.362152       {txt}Skewness      {res}-.6505721
{txt}99%    {res} 1.362152       1.362152       {txt}Kurtosis      {res} 2.962473
{txt}
{com}. 
. sum diversity, detail

                  {txt}Factor score (DIVERSITY)
{hline 61}
      Percentiles      Smallest
 1%    {res} -1.88719       -1.88719
{txt} 5%    {res}-1.239899       -1.88719
{txt}10%    {res}-.7892653       -1.88719       {txt}Obs         {res}    203,885
{txt}25%    {res}-.3033019       -1.88719       {txt}Sum of wgt. {res}    203,885

{txt}50%    {res} .1479928                      {txt}Mean          {res} .0379445
                        {txt}Largest       Std. dev.     {res} .6360977
{txt}75%    {res} .4713077       .9566104
{txt}90%    {res} .7946227       .9566104       {txt}Variance      {res} .4046203
{txt}95%    {res} .9566104       .9566104       {txt}Skewness      {res}-.8528272
{txt}99%    {res} .9566104       .9566104       {txt}Kurtosis      {res} 3.713913
{txt}
{com}. 
. sum diversity2, detail

                  {txt}Factor score (DIVERSITY)
{hline 61}
      Percentiles      Smallest
 1%    {res}-1.876142      -1.876142
{txt} 5%    {res}-1.232928      -1.876142
{txt}10%    {res}-.7831437      -1.876142       {txt}Obs         {res}    203,885
{txt}25%    {res}-.3015395      -1.876142       {txt}Sum of wgt. {res}    203,885

{txt}50%    {res} .1514713                      {txt}Mean          {res} .0394852
                        {txt}Largest       Std. dev.     {res} .6329339
{txt}75%    {res} .4714651       .9530694
{txt}90%    {res} .7930725       .9530694       {txt}Variance      {res} .4006053
{txt}95%    {res} .9530694       .9530694       {txt}Skewness      {res}-.8533153
{txt}99%    {res} .9530694       .9530694       {txt}Kurtosis      {res} 3.714317
{txt}
{com}. 
. corr justice justice2
{txt}(obs=203,885)

             {c |}  justice justice2
{hline 13}{c +}{hline 18}
     justice {c |}{res}   1.0000
    {txt}justice2 {c |}{res}   1.0000   1.0000

{txt}
{com}. 
. corr diversity diversity2 
{txt}(obs=203,885)

             {c |} divers~y divers~2
{hline 13}{c +}{hline 18}
   diversity {c |}{res}   1.0000
  {txt}diversity2 {c |}{res}   1.0000   1.0000

{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\J.PARK\Dropbox\Discrimination Project_for me\Organizational Diversity\2023 Version_Merging\FINAL\CFA_2014.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 8 Aug 2024, 13:21:18
{txt}{.-}
{smcl}
{txt}{sf}{ul off}